Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

        This paper deals with social responsibility visible to the media and the role they play in spreading the culture of environmental protection, and make research on a sample of the University of Baghdad consisting students from 150 students, male and female were distributed questionnaire form on the sample to obtain the required information has been questionnaire included axes distributed questions achieve the objectives of the search, and after the form data were analyzed using statistical program spss results show that the visual media and its role in spreading the culture of environmental protection form averages arithmetic high, indicating a rise in the influence of th

The present research aims to identify thecorrelation between cognitive motivation andthe trend towards the teaching profession among students of the Department of Chemistry in theFaculty of Education for Pure Sciences - Ibn al-Haytham, as well as to identify the differences in the relationship according to the variable type (male, female). The measures of cognitive motivation and the trend towards the teaching profession were applied, using pearson's correlation coefficient,t-testfor one sample, andthe t-test of two separate samples.

Abstract :

       The research aims to diagnose some of the negative phenomena
 ( Counterfiting , Pettifogging , Embezzlement ) that have been detected over the past ( 2010 – 2014 ), a fixed-term part of the national strategy for the fight against corruption launched by the Joint Council for the fight against corruption in Iraq and measuring the application of government control according to the American standard GAO standards and identifying the potential for the application of those standards gap. It has been collecting data and information of special issues of corruption reports and meeting with (42) employees and the use of a checklist has been prepared for thi

The Qur'an is an inexhaustible source for researchers, and all of them find a rich material for its research, and no wonder in it is the book of the greatest Arabic. Quranic research has been an attempt to extract the secret in the miracle of the Koran, and not the Quranic miracle is limited to the word and its meaning, but that the miracle extends to include every sound in motion or silent; the sound performance of the Quranic text increases the meaning of beauty and earns the word heartbeat, Souls; and this may be due to the beauty of voice in the performance and harmony between sounds and words, and harmony between the exits and descriptions, or the tides of the tides,
Based on the above and to show the miraculous aspects of the Qu

The Providence of the Rosaly's family to the Intellectual Movement in Yemen

MA Mahde, HAA Kadhim, HN Tarish…, Pakistan Heart Journal, 2023 - Cited by 4

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone